AI in #HCM can be defined as the application of smart technologies such as #artificialintelligence, #machinelearning, natural language processing (NLP), and deep learning to automate routine #HR tasks, deliver personalized experiences, and gain actionable insights from #HRdata.
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For #HRleaders, it is better business outcomes that is of primary interest. So, let’s dive into how AI in HCM can help HR teams deliver improved business outcomes.
How AI Improves HCM
(i) 6 Components of the Employee Lifecycle
1) #Talent Attraction: It begins even before a recruiter approaches a candidate with a profile. Talent attraction typically represents employer branding: the perception a potential candidate has about an employer. This perception could be shaped by word of mouth, general business performance (bullish stock performance or innovative product lineups), employee stories, and media coverage
2) #Recruitment: This begins with candidate sourcing and ends with an offer being made to the shortlisted candidate. As a huge chunk of recruitment becomes automated, the people focus moves from operational tasks to improving the candidate experience, boosting engagement, and selling the job to the candidate.
3) #Onboarding: Employee onboarding is perhaps the most critical driver of long-term engagement. Effective onboarding ensures that your new hires seamlessly integrate into the larger workforce and add real value to their work. Onboarding determines how productive your new hires will be.
4) #TalentDevelopment: Once your new hires are onboarded, how do you keep them engaged and become better at their jobs? Talent development includes everything from on-the-job training, to performance management, and succession planning. Data from performance reviews and weekly sign-ins provide valuable insights into employee competencies and skills which can then be mapped to their succession plan.
5) #Retention: It would be incorrect to look at employee retention in isolation from the other parts of the employee lifecycle. However, there are certain factors that impact retention more than others. For instance, employee benefits, stock options, and rewards are more likely to impact retention than, say, learning and development. With changing workforce demographics, retention will become more crucial as HR leaders look to justify the ROI of their HR strategy.
6) Separation: This is the last stage of the employee lifecycle and presents a terrific opportunity for HR teams to collect valuable data in the form of feedback and exit interviews. Also, past employees are perhaps one of the most important influencers when it comes to your employer brand. Employee stories greatly determine how your organization is perceived by candidates.
With AI in the loop, the employee lifecycle becomes easier to manage and influence. Let’s look at how AI is improving human capital management (HCM).
Essential Use-Cases of #AI in HCM
1) #TalentAcquisition: AI, when used in talent acquisition automates a large chunk of processes that relied on human recruiters. AI-driven talent acquisition also makes hiring more transparent, data-driven, and objective. From candidate sourcing to recruitment marketing, to interviewing and onboarding, AI has a significant impact on recruiter productivity and the candidate experience.
2) HR Service Delivery: AI-powered chatbots are changing how we interact with businesses in our consumer lives. The same principle holds good when it comes to interacting with your employer. AI-powered chatbots provide real-time, 24×7, support to employees. This effectively eliminates the need for HR professionals to attend to request/questions that employees ask. Additionally, the scalability of AI ensures that HR services can be delivered on mobile devices. Scott believes, good AI can effectively eliminate the need for HR intervention in employee self-service.
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